Papers by Ali Hakimi Parizi

3 papers
Joint Training for Learning Cross-lingual Embeddings with Sub-word Information without Parallel Corpora (2020.starsem-1)

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Challenge: Existing methods for learning cross-lingual word embeddings incorporate sub-word information during training.
Approach: They propose a method that incorporates sub-word information during training to learn cross-lingual word embeddings from monolingual data and a bilingual lexicon.
Outcome: The proposed method improves on bilingual lexicon induction, monolingual word similarity, and document classification using low-resource languages.
Evaluating Sub-word Embeddings in Cross-lingual Models (2020.lrec-1)

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Challenge: Existing approaches to learning sub-word embeddings for out-of-vocabulary words have not considered sub- word embedds in cross-lingual models.
Approach: They propose to use sub-word embeddings to form cross-lingual embeddables for out-of-vocabulary (OOV) words for which no embeddibles are available.
Outcome: The proposed bilingual lexicon induction task shows that sub-word embeddings can be leveraged to form cross-lingual embeddables for OOV words.
Evaluating a Joint Training Approach for Learning Cross-lingual Embeddings with Sub-word Information without Parallel Corpora on Lower-resource Languages (2021.starsem-1)

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Challenge: Cross-lingual word embeddings provide a way for information to be transferred between languages.
Approach: They propose a joint training approach that incorporates sub-word information during training to learn cross-lingual embeddings.
Outcome: The proposed method improves bilingual lexicon induction, especially for out-of-vocabulary words (OOVs) it is able to represent out- of-vocal words (OVs) and is more isomorphic than previous methods.

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